The field of data analysis and organization has become increasingly important as the volume and types of data increase. Data is used to track and represent things, people, events, actions, places, and more. Data is also collected in different circumstances.
In the Internet or the World Wide Web, for example, data is being passed between different users and websites. Users actions on the Internet are tracked, including which websites a user visits, which buttons a user clicks, what comments are posted by a user, and which keywords does a user input for searches. Interaction between websites, such as hyperlinks to one another, are also tracked. In the Internet environment, entities can be, for example, users, websites, servers, and hubs.
As another example, data can also be tracked in the healthcare field. The activities and identities of visitors, patients, and healthcare professionals within a hospital can be recorded as data. The interaction between illnesses, treatments, and the equipment used in the treatment may also be recorded as data. In the healthcare field, entities can be, for example, visitors, patients, healthcare professionals, hospitals, illnesses, treatments, and equipment.
In another example, data is tracked within the supply chain of goods and services. Buyers purchase goods or services from sellers. The goods or services may be provided by a manufacturer or another service entity. There can also be intermediary merchants. There are also shipments to deliver the goods and services. In such an environment, entities can be, for example, buyers, sellers, intermediary merchants, goods, services, manufacturers, service providers, and shipments.
It can be appreciated that in different circumstances, the identities of the entities and the types of data collected about the entities vary.
The collected data can be used to identify interactions between the entities. However, doing so is difficult when the amount of data is large.